Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

     Governmental establishments are maintaining historical data for job applicants for future analysis of predication, improvement of benefits, profits, and development of organizations and institutions. In e-government, a decision can be made about job seekers after mining in their information that will lead to a beneficial insight. This paper proposes the development and implementation of an applicant's appropriate job prediction system to suit his or her skills using web content classification algorithms (Logit Boost, j48, PART, Hoeffding Tree, Naive Bayes). Furthermore, the results of the classification algorithms are compared based on data sets called "job classification data" sets. Experimental results indicate

     This review explores the Knowledge Discovery Database (KDD) approach, which supports the bioinformatics domain to progress efficiently, and illustrate their relationship with data mining. Thus, it is important to extract advantages of Data Mining (DM) strategy management such as effectively stressing its role in cost control, which is the principle of competitive intelligence, and the role of it in information management. As well as, its ability to discover hidden knowledge. However, there are many challenges such as inaccurate, hand-written data, and analyzing a large amount of variant information for extracting useful knowledge by using DM strategies. These strategies are successfully applied in several applications as data wa

     The analysis of the hyperlink structure of the web has led to significant improvements in web information retrieval. This survey study evaluates and analyzes relevant research publications on link analysis in web information retrieval utilizing diverse methods. These factors include the research year, the aims of the research article, the algorithms utilized to complete their study, and the findings received after using the algorithms. The findings revealed that Page Rank, Weighted Page Rank, and Weighted Page Content Rank are extensively employed by academics to properly analyze hyperlinks in web information retrieval. Finally, this paper analyzes the previous studies.

     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

    Nowadays, the process of ontology learning for describing heterogeneous systems is an influential phenomenon to enhance the effectiveness of such systems using Social Network representation and Analysis (SNA). This paper presents a novel scenario for constructing adaptive architecture to develop community performance for heterogeneous communities as a case study. The crawling of the semantic webs is a new approach to create a huge data repository for classifying these communities. The architecture of the proposed system involves two cascading modules in achieving the ontology data, which is represented in Resource Description Framework (RDF) format. The proposed system improves the enhancement of these environments ach

The research deals with an analytical approach between new media and traditional one in the light of the changes imposed by technology, which has been able to change a number of common concepts in the field of communication and media. The researcher tries to find an analytical explanation of the relationship between technology by being an influential factor in building the information society, which is the basis of new media, and the technical output that influenced the forms of social relations and linguistic construction as a human communication tool. The research deals with an analytical approach between new media and traditional one in the light of the changes imposed by technology, which has been able to change a number of comm

The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content.   When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniqu